Agent and cyber-physical system based self-organizing and self-adaptive intelligent shopfloor

The increasing demand of customized production results in huge challenges to the traditional manufacturing systems. In order to allocate resources timely according to the production requirements and to reduce disturbances, a framework for the future intelligent shopfloor is proposed in this paper. The framework consists of three primary models, namely the model of smart machine agent, the self-organizing model, and the self-adaptive model. A cyber-physical system for manufacturing shopfloor based on the multiagent technology is developed to realize the above-mentioned function models. Gray relational analysis and the hierarchy conflict resolution methods were applied to achieve the self-organizing and self-adaptive capabilities, thereby improving the reconfigurability and responsiveness of the shopfloor. A prototype system is developed, which has the adequate flexibility and robustness to configure resources and to deal with disturbances effectively. This research provides a feasible method for designing an autonomous factory with exception-handling capabilities

Intelligent systems in manufacturing: current developments and future prospects

Global competition and rapidly changing customer requirements are demanding increasing changes in manufacturing environments. Enterprises are required to constantly redesign their products and continuously reconfigure their manufacturing systems. Traditional approaches to manufacturing systems do not fully satisfy this new situation. Many authors have proposed that artificial intelligence will bring the flexibility and efficiency needed by manufacturing systems. This paper is a review of artificial intelligence techniques used in manufacturing systems. The paper first defines the components of a simplified intelligent manufacturing systems (IMS), the different Artificial Intelligence (AI) techniques to be considered and then shows how these AI techniques are used for the components of IMS

Special Session on Industry 4.0

No abstract available

Aplikácia kognitivného modelu vizuálnej pozornosti v automatizovanej montáži

Zásobovacie zariadenia a podsystémy v štruktúrach montážnych systémov majú významné postavenie. Technickú zložitosť klasických zásobovacích zariadení a podsystémov je možné eliminovať pružnými programovateľnými automatizovanými zariadeniami. Informácie o spomínanom objekte zabezpečované senzorovými modulmi sa spracovávajú v riadiacom systéme zariadenia resp. na vyššej úrovni riadenia montážneho systému. Spracované informácie sú distribuované ako riadiace informácie výkonným jednotkám a prvkom, ktoré vykonávajú príslušné funkcie. Riadiace systémy programovateľných zásobovacích zariadení a podsystémov plnia viaceré funkcie napr. spracovanie informácií od senzorových jednotiek a modulov, správne vyhodnotenie polohy súčiastky a určenie postupu činnosti výkonných jednotiek a prvkov, distribúcia výkonných inštrukcií pohonovým jednotkám, atď. Programové vybavenie založené na využívaní kognitívneho modelu vizuálnej pozornosti charakterizuje nový prístup k riešeniu uvádzaných problémov. Pri vizuálnom vnímání scény obsahujúcej rôzne objekty a pre potrebu interakcie s určitým cieľovým objektom nachádzajúcim sa v tejto scéne je nutné aby systém upriamil svoju pozornosť na tento (cieľový) objekt. Tento mechanizmus je jedným z principiálnych prvkov videnia a podobne ako mnoho biologicky motivovaných systémov je veľmi výhodne využiteľný v praxi. Navrhovaný model je implementáciou mechanizmu vizuálnej pozornosti vo vytvorenom počítačom simulovanom prostredí.Logistic devices and sub - systems in the structures of assembly systems have significant position. Technical complexity of classical devices and sub - systems can be decreased by using of flexible programmable automated devices. Information's about objects provided by sensor modules are handled in processing system of the device, respective on the higher level of the assembly system. Executed information is distributed like processing information to executive units and elements. Control systems of programmable supply devices and sub - systems take handle of many functions, for example: processing information from sensor devices and modules, right calculating of the bearing of the component, distributing of executive instructions to actuating units, and many others. Software accessories based on the using of cognitive model of visual attention featured a new way of solving former problems. By visual reception the scenes contains miscellaneous objects and for the demand of the interaction with the target object is necessary that the system is need to be focused to this object. This mechanism is one of the pricipally elements of vision, and like many biologically motivated systems is very useful in practice. Designed model is an implementation of the mechanism of visual attention in the computer created simulation environment

NASA Center for Intelligent Robotic Systems for Space Exploration

NASA's program for the civilian exploration of space is a challenge to scientists and engineers to help maintain and further develop the United States' position of leadership in a focused sphere of space activity. Such an ambitious plan requires the contribution and further development of many scientific and technological fields. One research area essential for the success of these space exploration programs is Intelligent Robotic Systems. These systems represent a class of autonomous and semi-autonomous machines that can perform human-like functions with or without human interaction. They are fundamental for activities too hazardous for humans or too distant or complex for remote telemanipulation. To meet this challenge, Rensselaer Polytechnic Institute (RPI) has established an Engineering Research Center for Intelligent Robotic Systems for Space Exploration (CIRSSE). The Center was created with a five year $5.5 million grant from NASA submitted by a team of the Robotics and Automation Laboratories. The Robotics and Automation Laboratories of RPI are the result of the merger of the Robotics and Automation Laboratory of the Department of Electrical, Computer, and Systems Engineering (ECSE) and the Research Laboratory for Kinematics and Robotic Mechanisms of the Department of Mechanical Engineering, Aeronautical Engineering, and Mechanics (ME,AE,&M), in 1987. This report is an examination of the activities that are centered at CIRSSE